Sensor-assisted antenna and beam selection for wireless communications

ABSTRACT

A wireless device is configured to select a beam and/or an antenna based on detection a detected position and/or orientation of the device relative to a remote device. The device obtains motion data indicating a change in position or orientation of the wireless device. The device determines its pose relative to the remote device. The device accesses a coverage map that associates, for each potential pose for the device with respect to the remote device: an antenna for communicating with the remote device and/or a beam for communicating with the remote device. The device selects a particular antenna and/or a particular beam for communicating with the remote device; and causes transmission or reception of data to or from the remote device by the particular antenna and/or the particular beam.

CLAIM OF PRIORITY

This application claims priority under 35 U.S.C. § 119(e) to U.S. PatentApplication Ser. No. 63/135,503, filed on Jan. 8, 2021, the entirecontents of which are hereby incorporated by reference.

TECHNICAL FIELD

This disclosure relates generally to wireless communications.

BACKGROUND

Wireless devices can include phased array antennas for transmittingsignals to and receiving signals from remote devices (e.g., in awireless network). A phased array includes a computer-controlled arrayof antennas that creates a beam of radio waves that can beelectronically steered to point in different directions without movingthe antennas.

Beamforming or spatial filtering is a signal processing technique usedin sensor arrays for directional signal transmission or reception. Thisis achieved by combining elements in an antenna array in such a way thatsignals at particular angles experience constructive interference whileothers experience destructive interference. Beamforming can be used atboth the transmitting and receiving ends (e.g., by phased arrayantennas) in order to achieve spatial selectivity. Beamforming allowsmmWave devices to steer radio frequency (RF) energy at a particulardirection, overcoming mmWave propagation loss. Beams are typically fixedand designed a-priori in codebooks such as phase-amplitude combinationsfor antenna elements.

SUMMARY

This application describes systems and processes for sensor-assistedantenna and beam selection for wireless networks. Generally, thewireless networks include transmissions using the millimeter wave(mmWave) spectrum. For example, the mmWave spectrum can be used forFifth Generation (5G) and/or Long Term Evolution (LTE) networks formmWave frequency ranges (e.g., frequency range 2 (FR2), frequency range3 (FR3), etc.) transmissions from base stations (e.g., next generationnodes (gNB)) or to and from client devices (e.g., mobile devicesdescribed throughout this description). In general, FR2 transmissionsare between 24.25 GHz to 52.6 GHz. Generally, mmWave high bandwidth(e.g., about 400 MHz) transmissions have a relatively high propagationloss. For example, mmWave transmissions can have a 20 dB loss relativeto sub 6 GHz bands, such as those used for frequency range 1 (FR1)transmissions.

To overcome this loss, mmWave-enabled devices described herein areconfigured for beamforming, beam management, and antenna selection basedon sensor feedback of one or more sensors of the mmWave-enabled device.Beamforming enables a device to steer the radiofrequency (RF) energy ina particular direction. The transmitting device forms a beam by varyingan amplitude and/or a phase of one or more elements of a phased arrayantenna. Generally, the transmitting device generates a beam based onpredefined phase-amplitude combinations for each antenna of the array toensure that a narrow beam of relatively high power is transmitted in adesired direction with respect to the phased array antenna. Beammanagement enables a device to identify an optical beam for transmissionin each of the uplink and downlink directions. Antenna selection enablesan mmWave-enabled device (e.g., a user equipment (UE)) to ensurehigh-speed connectivity by improving wireless coverage for a givenuplink or downlink transmission. The systems and processes forsensor-assisted antenna and beam selection are configured to usefeedback from sensors on the mmWave-enabled devices to optimizebeamforming, beam management, and antenna selection and thereforemitigate propagation loss, increase efficiency in beam determinationregarding time and/or resources, and improve link performance.

The sensors on the mmWave-enabled devices are configured to provide dataindicates how the device has moved in an environment. The motion datafrom the sensors enables the device to estimate beamforming parametersand antenna selection for an optimal connection based on previous dataindicating a strong signal. This allows the device to estimate optimalparameters for determining an antenna selection without performing afull sweep of the possible beams and antenna to test variouscombinations of beams and antenna for optimal performance. Therefore,the device can determine a likely candidate for a relativelyhigh-performance connection in a quick manner without the bandwidthoverhead of performing a sweep of beam and antenna combinations.

The systems and processes described in this document enable one or moreof the following advantages. The systems and processes are configured toinstantly (or nearly instantly) identify a best beam and antenna panelfor a UE with a relatively low scanning overhead. Generally, beam andantenna selection algorithms are configured to identify best beam andantenna panel settings at runtime. However, beam selection and antennaselection can result in relatively high scanning transmission overheads.For example, mmWave devices can be equipped with multiple antenna panels(e.g., three or more). Each antenna supports tens of beams. As such,scanning each available beam for each antenna panels can require tens ofmilliseconds, which adds prohibitive overheads to the network. This isespecially prohibitive for augmented reality/virtual reality (AR/VR)applications, which have 1-2 millisecond latency requirements. Frequentbeam and antenna scanning is not optimal practical for wireless devices.The processes and systems for sensor-assisted antenna and beam selectionenable selection of the beam and antenna using a reduced frequency ofscanning and thus with a reduced network overhead (and thus a reducedcommunication latency).

The processes and systems for sensor-assisted antenna and beam selectionenable a UE or other similar device to overcome changes to theenvironment of the UE and allow for increased mobility of the UE (whichcan represent a change in an environment of the UE). For example, adevice using mmWave communication may frequently adjust beam and antennaselection in response to physical changes in the environment of thedevice (e.g., moving cars or trees) or movement of the device. Changesin the environment may cause blockages in a communication path of the UEor changes in location of the remote device (e.g., a node) incommunication with the UE. This can cause the UE and/or node tofrequently adjust its beams to achieve a better performance for acommunications link. The processes and systems for sensor-assistedantenna and beam selection enable the mmWave devices in the environmentto quickly (e.g., instantly or nearly instantly) determine an optimalbeam selection and/or antenna selection (when applicable) for improvedperformance on the communications link in response to theseenvironmental changes and/or movement of one or both of thecommunicating devices.

The one or more advantages previously described can be enabled by one ormore embodiments.

In a general aspect, a process includes obtaining motion data from oneor more motion sensors coupled to a wireless device, the motion dataindicating a change in position or orientation of the wireless device.The process includes determining, based on the motion data, a pose ofthe wireless device relative to a remote device. The process includesselecting a particular antenna or a particular beam for communicatingwith the remote device based on a coverage map that associates, for eachpose of a plurality of poses of the wireless device with respect to theremote device: an antenna for communicating with the remote device; abeam for communicating with the remote device; or both the antenna andthe beam configuration for communicating with the remote device. Theprocess includes causing transmission or reception of data to or fromthe remote device by the particular antenna or the particular beam.

In an embodiment, the process includes determining an initial pose ofthe wireless device with respect to the remote device using angle ofarrival (AoA) data, wherein the pose of the wireless device relative tothe remote device is based on the motion data indicative of the changein the position or the orientation of the wireless device from theinitial pose.

In an embodiment, the motion data is indicative of no change to theposition or orientation of the wireless device over a period of time.The process includes determining that one or more metrics of acommunication channel between the wireless device and the remote devicefail to satisfy one or more respective thresholds; in response todetermining, identifying an angle of arrival (AoA) value of a strongestsignal from the remote device; and identifying, from the coverage map,the particular beam and the particular antenna as being associated withthe AoA value in the coverage map.

In an embodiment, the one or more metrics include at least one of asignal to noise (SNR) ratio of a signal received from the remote device,a delay spread value of the signal, and a magnitude of a change in theAoA of the signal.

In an embodiment, the coverage map indicates that the particular antennaand the particular beam represent the highest gain for causingtransmission of data to the remote device or receiving additional datafrom the remote device.

In an embodiment, the one or more motion sensors comprise at least anaccelerometer, a gyroscope, or both the accelerometer and the gyroscope.

In an embodiment, the wireless device and the remote device areconfigured for mmWave communication using frequency range 2 (FR2).

In an embodiment, selecting the particular antenna and the particularbeam for communicating with the remote device is performed with alatency of less than 2 milliseconds.

In an embodiment, the process includes retrieving motion dataperiodically to determine if the wireless device is moving or is static.

In an embodiment, the wireless device comprises at least three antennaarrays, and wherein each antenna array includes at least 10 beamconfigurations.

In an embodiment, determining, based on the motion data, the pose of thewireless device relative to the remote device includes determining oneor more of a translational motion or a rotational motion of the wirelessdevice exceeds a motion threshold; and in response to determining thatthe motion threshold is exceeded, accessing the coverage map.

In an embodiment, the process includes comparing the change in positionor orientation of the wireless device to a threshold change value; andin response to the comparing, accessing the coverage map when the changeexceeds the threshold.

In an embodiment, the process includes detecting that a signal strengthreceived from the remote device is below a threshold signal strength;and in response to detecting, obtaining the motion data.

In an embodiment, the process includes selecting a particular antennaand or a particular beam for communicating with the remote device basedon the coverage map; and causing transmission or reception of data to orfrom the remote device by the particular antenna and the particularbeam.

In a general aspect, a wireless device includes at least one motionsensor; one or more antenna arrays each configured for at least two beamconfigurations; one or more processors; and a non-transitorycomputer-readable storage medium storing instructions which, whenexecuted by the one or more processors, cause the one or more processorsto perform operations. In an embodiment, the operations includeobtaining motion data from the at least one motion sensor, the motiondata indicating a change in position or orientation of the wirelessdevice. In an embodiment, the operations include determining, based onthe motion data, a pose of the wireless device relative to a remotedevice. In an embodiment, the operations include selecting a particularantenna and a particular beam for communicating with the remote devicebased on a coverage map that associates, for each pose of a plurality ofposes of the wireless device with respect to the remote device: anantenna array of the one or more antenna arrays for communicating withthe remote device; a beam for communicating with the remote device; orboth the antenna and the beam for communicating with the remote device.In an embodiment, the operations include causing transmission of data tothe remote device by the particular antenna and the particular beam.

In an embodiment, the operations include determining an initial pose ofthe wireless device with respect to the remote device using angle ofarrival (AoA) data, wherein the pose of the wireless device relative tothe remote device is based on the motion data indicative of the changein the position or the orientation of the wireless device from theinitial pose.

In an embodiment, the motion data is indicative of no change to theposition or orientation of the wireless device over a period of time,and the operations further comprise: determining that one or moremetrics of a communication channel between the wireless device and theremote device fail to satisfy one or more respective thresholds; inresponse to determining, identifying an angle of arrival (AoA) value ofa strongest signal from the remote device; and identifying, from thecoverage map, the particular beam and the particular antenna as beingassociated with the AoA value in the coverage map.

In an embodiment, the one or more metrics include at least one of asignal to noise (SNR) ratio of a signal from the remote device, a delayspread value of the signal, and a magnitude of a change in the AoA ofthe signal.

In an embodiment, the coverage map indicates that the particular antennaand the particular beam represent the highest gain for causingtransmission of data to the remote device or receiving additional datafrom the remote device.

In an embodiment, the one or more motion sensors comprise at least anaccelerometer, a gyroscope, or both the accelerometer and the gyroscope.

In an embodiment, the wireless device and the remote device areconfigured for mmWave communication using frequency range 2 (FR2).

In an embodiment, the operations include comparing the change inposition or orientation of the wireless device to a threshold changevalue; in response to the comparing, accessing the coverage map when thechange exceeds the threshold.

In an embodiment, the operations include detecting that a signalstrength received from the remote device is below a threshold signalstrength; and in response to detecting, obtaining the motion data.

In an embodiment, the operations include selecting a particular antennaand or a particular beam for communicating with the remote device basedon the coverage map; and causing transmission or reception of data to orfrom the remote device by the particular antenna and the particularbeam.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. The techniquesdescribed here can be implemented by one or more wireless communicationsystems, components of a wireless communication system (e.g., a station,an access point, a user equipment, a base station, etc.), or othersystems, devices, methods, or non-transitory computer-readable media,among others. Other features and advantages will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 illustrates an example wireless communication system, accordingto various embodiments herein.

FIG. 2 illustrates an example of a platform or device configured forsensor-assisted antenna and beam selection in accordance with someimplementations of the present disclosure.

FIG. 3 illustrates an example device configured for multiusertrigger-based wireless communications in accordance with someimplementations of the present disclosure.

FIGS. 4A-4C illustrates an example of a coverage map for selection ofone or more of an antenna and a beam in accordance with someimplementations of the present disclosure.

FIG. 5 illustrates an example of selection of one or more of an antennaand a beam based on sensor feedback in accordance with someimplementations of the present disclosure.

FIG. 6 illustrates an example of selection of one or more of an antennaand a beam based on sensor feedback in accordance with someimplementations of the present disclosure.

FIG. 7 illustrates an example process for configuration of parametersfor selection of a beam, a beam, or both based on sensor feedback inaccordance with some implementations of the present disclosure.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

The techniques described here enable a wireless device to perform beamselection, antenna selection, or both beam and antenna selection inresponse to changes to the channel of a communications link. A deviceincludes one or more sensors that provide motion data to the device. Thedevice is configured to perform beamforming, select an antenna fortransmission, or both perform beamforming and select an antenna fortransmission in response to receiving the motion data. This enables thedevice to perform beamforming and antenna selection to improvecommunication performance using less bandwidth overhead and with lesslatency than performing full scanning of beams an antenna of the device.

Generally, the beam and antenna selection are performed to improvecommunication bandwidth in the context of mmWave systems (e.g., usingFR2 frequencies, FR3 frequencies, or other mmWave frequencies). mmWavecommunication links have a relatively high propagation loss over longdistances (e.g., over 10s or 100s of meters) relative to losses for FR1links. To mitigate propagation loss and improve performance of acommunication link, mmWave-enabled devices are configured forbeamforming, beam management, and antenna selection based on sensorfeedback of one or more sensors of the mmWave-enabled device.

Beamforming enables a device to steer the radiofrequency (RF) energy ina particular direction. The transmitting device forms a beam by varyingan amplitude and/or a phase of one or more elements of a phased arrayantenna. Generally, the transmitting device generates a beam based onpredefined phase-amplitude combinations for each antenna of the array toensure that a narrow beam of relatively high power is transmitted in adesired direction with respect to the phased array antenna.

Beam management enables a device to identify an optimal beam fortransmission in each of the uplink and downlink directions. In anexample, for 5G NR mmWave transmissions, a node (e.g., a gNB) transmitssynchronization signals periodically (e.g., between 5 to 160 millisecond(monitoring system) periods) to identify best transmit and receivebeams. This includes an initial beam training step using multiple beams.In this first step, a wide sweeping range is covered using wider beamwidths. A second step includes a beam refinement step. In this step, theUE sweeps over narrower beams over a narrower range than in the firststep. This enables the UE to hone in on the desired beam direction. Inthe third step, the device is configured for beam refinement. In thebeam refinement step, a user equipment (UE) performs tuning of thereceive angle for the beam, and the node transmits using a fixed beam.The UE measures different signal strengths until an optimalconfiguration of the beams is found. In an example, for a 802.11ad/aymmWave transmission, an access point (AP) and a wireless device (e.g., aUE) train their respective beams during sector level sweep (SLS) and thebeam refinement process (BRP) as defined in 802.11 standards.

Antenna selection enables a device (e.g., a UE) to ensure high-speedconnectivity by improving wireless coverage for a given uplink ordownlink transmission. In an example, either of a blockage of a firstantenna or an antenna misalignment can cause throughput levels todecrease relative to an ideal transmission environment. In this case,the UE is configured to select from a plurality of phased antenna arrays(also called antenna panels).

The mmWave-enabled devices include one or more sensors configured toprovide motion data. The motion data indicates how the device has movedin an environment. The motion data from the sensors enables the deviceto estimate beamforming parameters and antenna selection for an optimalconnection based on previous data indicating a strong signal. Thisallows the device to estimate optimal parameters for beamforming anantenna selection without performing a full sweep of the possible beamsand antenna to test various combinations of beams and antenna foroptimal performance. Therefore, the device can determine a likelycandidate for a relatively high-performance connection in a quick mannerwithout the bandwidth overhead of performing a sweep of beam and antennacombinations. For example, if an mmWave-enabled device (e.g., a UE) isturned 180 degrees, the system can estimate that the direction of thebeamforming may be 180 degrees from the previous direction for whichoptimal transmission performance was determined. Additional examples ofthis process are subsequently described in relation to the figures. Thesystems and processes described are compatible with any mmWavetechnologies (e.g., 802.11ad/ay, 5G, etc.). The system is lightweightand is configured to select a beam, antenna, or both independent of anyantenna or beam scanning.

FIG. 1 illustrates an example wireless communication system 100. Forpurposes of convenience and without limitation, the example system 100is described in the context of the LTE and 5G NR communication standardsas defined by the Third Generation Partnership Project (3GPP) technicalspecifications. More specifically, the wireless communication system 100is described in the context of a Non-Standalone (NSA) networks thatincorporate both LTE and NR, for example, E-UTRA (Evolved UniversalTerrestrial Radio Access)-NR Dual Connectivity (EN-DC) networks, andNE-DC networks. However, the wireless communication system 100 may alsobe a Standalone (SA) network that incorporates only NR. Furthermore,other types of communication standards are possible, including future3GPP systems (e.g., Sixth Generation (6G)) systems, IEEE 802.16protocols (e.g., WMAN, WiMAX, etc.), or the like.

The system 100 includes UE 101 a and UE 101 b (collectively referred toas the “UEs 101”). In this example, the UEs 101 are illustrated assmartphones (e.g., handheld touchscreen mobile computing devicesconnectable to one or more cellular networks). In other examples, any ofthe UEs 101 may include other mobile or non-mobile computing devices,such as consumer electronics devices, cellular phones, smartphones,feature phones, tablet computers, wearable computer devices, personaldigital assistants (PDAs), pagers, wireless handsets, desktop computers,laptop computers, in-vehicle infotainment (IVI), in-car entertainment(ICE) devices, an Instrument Cluster (IC), head-up display (HUD)devices, onboard diagnostic (OBD) devices, dashtop mobile equipment(DME), mobile data terminals (MDTs), Electronic Engine Management System(EEMS), electronic/engine control units (ECUs), electronic/enginecontrol modules (ECMs), embedded systems, microcontrollers, controlmodules, engine management systems (EMS), networked or “smart”appliances, machine-type communications (MTC) devices,machine-to-machine (M2M) devices, Internet of Things (IoT) devices, orcombinations of them, among others.

In some examples, any of the UEs 101 may be IoT UEs, which can include anetwork access layer designed for low-power IoT applications utilizingshort-lived UE connections. An IoT UE can utilize technologies such asM2M or MTC for exchanging data with an MTC server or device using, forexample, a public land mobile network (PLMN), proximity services(ProSe), device-to-device (D2D) communication, sensor networks, IoTnetworks, or combinations of them, among others. The M2M or MTC exchangeof data may be a machine-initiated exchange of data. An IoT networkdescribes interconnecting IoT UEs, which may include uniquelyidentifiable embedded computing devices (within the Internetinfrastructure), with short-lived connections. The IoT UEs may executebackground applications (e.g., keep-alive messages or status updates) tofacilitate the connections of the IoT network.

The UEs 101 are configured to connect (e.g., communicatively couple)with an access network (AN) or radio access network (RAN) 110. In someexamples, the RAN 110 may be a next generation RAN (NG RAN), an evolvedUMTS terrestrial radio access network (E-UTRAN), or a legacy RAN, suchas a UMTS terrestrial radio access network (UTRAN) or a GSM EDGE radioaccess network (GERAN). As used herein, the term “NG RAN” may refer to aRAN 110 that operates in a 5G NR system 100, and the term “E-UTRAN” mayrefer to a RAN 110 that operates in an LTE or 4G system 100.

To connect to the RAN 110, the UEs 101 utilize connections (or channels)103 and 104, respectively, each of which may include a physicalcommunications interface or layer, as described below. In this example,the connections 103 and 104 are illustrated as an air interface toenable communicative coupling, and can be consistent with cellularcommunications protocols, such as a global system for mobilecommunications (GSM) protocol, a code-division multiple access (CDMA)network protocol, a push-to-talk (PTT) protocol, a PTT over cellular(POC) protocol, a universal mobile telecommunications system (UMTS)protocol, a 3GPP LTE protocol, a 5G NR protocol, or combinations ofthem, among other communication protocols. In some examples, the UEs 101may directly exchange communication data using an interface 105, such asa ProSe interface. The interface 105 may alternatively be referred to asa sidelink interface 105 and may include one or more logical channels,such as a physical sidelink control channel (PSCCH), a physical sidelinkshared channel (PSSCH), a physical sidelink downlink channel (PSDCH), ora physical sidelink broadcast channel (PSBCH), or combinations of them,among others.

The UE 101 b is shown to be configured to access an access point (AP)106 (also referred to as “WLAN node 106,” “WLAN 106,” “WLAN Termination106,” “WT 106” or the like) using a connection 107. The connection 107can include a local wireless connection, such as a connection consistentwith any IEEE 802.11 protocol, in which the AP 106 would include awireless fidelity (Wi-Fi®) router. In this example, the AP 106 is shownto be connected to the Internet without connecting to the core networkof the wireless system, as described in further detail below. In variousexamples, the UE 101 b, RAN 110, and AP 106 may be configured to useLTE-WLAN aggregation (LWA) operation or LTW/WLAN radio level integrationwith IPsec tunnel (LWIP) operation. The LWA operation may involve the UE101 b in RRC CONNECTED being configured by a RAN node 111 a, 111 b toutilize radio resources of LTE and WLAN. LWIP operation may involve theUE 101 b using WLAN radio resources (e.g., connection 107) using IPsecprotocol tunneling to authenticate and encrypt packets (e.g., IPpackets) sent over the connection 107. IPsec tunneling may includeencapsulating the entirety of original IP packets and adding a newpacket header, thereby protecting the original header of the IP packets.

The RAN 110 can include one or more AN nodes or RAN nodes 111 a and 111b (collectively referred to as “RAN nodes 111” or “RAN node 111”) thatenable the connections 103 and 104. As used herein, the terms “accessnode,” “access point,” or the like may describe equipment that providesthe radio baseband functions for data or voice connectivity, or both,between a network and one or more users. These access nodes can bereferred to as base stations (BS), gNodeBs, gNBs, eNodeBs, eNBs, NodeBs,RAN nodes, rode side units (RSUs), transmission reception points (TRxPsor TRPs), and the link, and can include ground stations (e.g.,terrestrial access points) or satellite stations providing coveragewithin a geographic area (e.g., a cell), among others. As used herein,the term “NG RAN node” may refer to a RAN node 111 that operates in an5G NR system 100 (for example, a gNB), and the term “E-UTRAN node” mayrefer to a RAN node 111 that operates in an LTE or 4G system 100 (e.g.,an eNB). In some examples, the RAN nodes 111 may be implemented as oneor more of a dedicated physical device such as a macrocell base station,or a low power (LP) base station for providing femtocells, picocells orother like cells having smaller coverage areas, smaller user capacity,or higher bandwidth compared to macrocells.

In some examples, some or all of the RAN nodes 111 may be implemented asone or more software entities running on server computers as part of avirtual network, which may be referred to as a cloud RAN (CRAN) or avirtual baseband unit pool (vBBUP). The CRAN or vBBUP may implement aRAN function split, such as a packet data convergence protocol (PDCP)split in which radio resource control (RRC) and PDCP layers are operatedby the CRAN/vBBUP and other layer two (e.g., data link layer) protocolentities are operated by individual RAN nodes 111; a medium accesscontrol (MAC)/physical layer (PHY) split in which RRC, PDCP, MAC, andradio link control (RLC) layers are operated by the CRAN/vBBUP and thePHY layer is operated by individual RAN nodes 111; or a “lower PHY”split in which RRC, PDCP, RLC, and MAC layers and upper portions of thePHY layer are operated by the CRAN/vBBUP and lower portions of the PHYlayer are operated by individual RAN nodes 111. This virtualizedframework allows the freed-up processor cores of the RAN nodes 111 toperform, for example, other virtualized applications. In some examples,an individual RAN node 111 may represent individual gNB distributedunits (DUs) that are connected to a gNB central unit (CU) usingindividual F1 interfaces (not shown in FIG. 1). In some examples, thegNB-DUs may include one or more remote radio heads or RFEMs (see, e.g.,FIG. 2), and the gNB-CU may be operated by a server that is located inthe RAN 110 (not shown) or by a server pool in a similar manner as theCRAN/vBBUP. Additionally or alternatively, one or more of the RAN nodes111 may be next generation eNBs (ng-eNBs), including RAN nodes thatprovide E-UTRA user plane and control plane protocol terminations towardthe UEs 101, and are connected to a 5G core network (e.g., core network120) using a next generation interface.

In vehicle-to-everything (V2X) scenarios, one or more of the RAN nodes111 may be or act as RSUs. The term “Road Side Unit” or “RSU” refers toany transportation infrastructure entity used for V2X communications. ARSU may be implemented in or by a suitable RAN node or a stationary (orrelatively stationary) UE, where a RSU implemented in or by a UE may bereferred to as a “UE-type RSU,” a RSU implemented in or by an eNB may bereferred to as an “eNB-type RSU,” a RSU implemented in or by a gNB maybe referred to as a “gNB-type RSU,” and the like. In some examples, anRSU is a computing device coupled with radio frequency circuitry locatedon a roadside that provides connectivity support to passing vehicle UEs101 (vUEs 101). The RSU may also include internal data storage circuitryto store intersection map geometry, traffic statistics, media, as wellas applications or other software to sense and control ongoing vehicularand pedestrian traffic. The RSU may operate on the 5.9 GHz Direct ShortRange Communications (DSRC) band to provide very low latencycommunications required for high speed events, such as crash avoidance,traffic warnings, and the like. Additionally or alternatively, the RSUmay operate on the cellular V2X band to provide the aforementioned lowlatency communications, as well as other cellular communicationsservices. Additionally or alternatively, the RSU may operate as a Wi-Fihotspot (2.4 GHz band) or provide connectivity to one or more cellularnetworks to provide uplink and downlink communications, or both. Thecomputing device(s) and some or all of the radiofrequency circuitry ofthe RSU may be packaged in a weatherproof enclosure suitable for outdoorinstallation, and may include a network interface controller to providea wired connection (e.g., Ethernet) to a traffic signal controller or abackhaul network, or both.

Any of the RAN nodes 111 can terminate the air interface protocol andcan be the first point of contact for the UEs 101. In some examples, anyof the RAN nodes 111 can fulfill various logical functions for the RAN110 including, but not limited to, radio network controller (RNC)functions such as radio bearer management, uplink and downlink dynamicradio resource management and data packet scheduling, and mobilitymanagement.

In some examples, the UEs 101 can be configured to communicate usingorthogonal frequency division multiplexing (OFDM) communication signalswith each other or with any of the RAN nodes 111 over a multicarriercommunication channel in accordance with various communicationtechniques, such as, but not limited to, OFDMA communication techniques(e.g., for downlink communications) or SC-FDMA communication techniques(e.g., for uplink and ProSe or sidelink communications), although thescope of the techniques described here not limited in this respect. TheOFDM signals can comprise a plurality of orthogonal subcarriers.

In some examples, a downlink resource grid can be used for downlinktransmissions from any of the RAN nodes 111 to the UEs 101, while uplinktransmissions can utilize similar techniques. The grid can be atime-frequency grid, called a resource grid or time-frequency resourcegrid, which is the physical resource in the downlink in each slot. Sucha time-frequency plane representation is a common practice for OFDMsystems, which makes it intuitive for radio resource allocation. Eachcolumn and each row of the resource grid corresponds to one OFDM symboland one OFDM subcarrier, respectively. The duration of the resource gridin the time domain corresponds to one slot in a radio frame. Thesmallest time-frequency unit in a resource grid is denoted as a resourceelement. Each resource grid comprises a number of resource blocks, whichdescribe the mapping of certain physical channels to resource elements.Each resource block comprises a collection of resource elements; in thefrequency domain, this may represent the smallest quantity of resourcesthat currently can be allocated. There are several different physicaldownlink channels that are conveyed using such resource blocks.

In some examples, the UEs 101 and the RAN nodes 111 communicate (e.g.,transmit and receive) data over a licensed medium (also referred to asthe “licensed spectrum” or the “licensed band”) and an unlicensed sharedmedium (also referred to as the “unlicensed spectrum” or the “unlicensedband”). The licensed spectrum may include channels that operate in thefrequency range of approximately 400 MHz to approximately 3.8 GHz,whereas the unlicensed spectrum may include the 5 GHz band. NR in theunlicensed spectrum may be referred to as NR-U, and LTE in an unlicensedspectrum may be referred to as LTE-U, licensed assisted access (LAA), orMulteFire.

FIG. 2 illustrates an example of a platform 300 (or “device 300”). Insome examples, the computer platform 300 may be suitable for use as UEs101 or any other component or device discussed herein. The platform 300may include any combinations of the components shown in the example. Thecomponents of platform 300 (or portions thereof) may be implemented asintegrated circuits (ICs), discrete electronic devices, or othermodules, logic, hardware, software, firmware, or a combination of themadapted in the computer platform 300, or as components otherwiseincorporated within a chassis of a larger system. The block diagram ofFIG. 2 is intended to show a high level view of components of theplatform 300. However, in some examples, the platform 300 may includefewer, additional, or alternative components, or a different arrangementof the components shown in FIG. 2.

The data processing device 302 includes circuitry such as, but notlimited to, one or more processors (or processor cores), cache memory,and one or more of LDOs, interrupt controllers, serial interfaces suchas SPI, I2C or universal programmable serial interface module, RTC,timer-counters including interval and watchdog timers, general purposeI/O, memory card controllers such as SD MMC or similar, USB interfaces,MIPI interfaces, and JTAG test access ports. The processors (or cores)of the data processing device 302 may be coupled with or may includememory/storage elements and may be configured to execute instructionsstored in the memory or storage to enable various applications oroperating systems to run on the system 300. In some examples, the memoryor storage elements may be on-chip memory circuitry, which may includeany suitable volatile or non-volatile memory, such as DRAM, SRAM, EPROM,EEPROM, Flash memory, solid-state memory, or combinations of them, amongother types of memory.

The processor(s) of data processing device 302 may include, for example,one or more processor cores, one or more application processors, one ormore GPUs, one or more RISC processors, one or more ARM processors, oneor more CISC processors, one or more DSP, one or more FPGAs, one or morePLDs, one or more ASICs, one or more microprocessors or controllers, amultithreaded processor, an ultra-low voltage processor, an embeddedprocessor, some other known processing element, or any suitablecombination thereof. In some examples, the data processing device 302may include, or may be, a special-purpose processor/controller to carryout the techniques described herein.

As examples, the processor(s) of data processing device 302 may includean Apple A-series processor. The processors of the data processingdevice 302 may also be one or more of an Intel® Architecture Core™ basedprocessor, such as a Quark™, an Atom™ an i3, an i5, an i7, or anMCU-class processor, or another such processor available from Intel®Corporation, Santa Clara, Calif.; Advanced Micro Devices (AMD) Ryzen®processor(s) or Accelerated Processing Units (APUs); Snapdragon™processor(s) from Qualcomm® Technologies, Inc., Texas Instruments, Inc.®Open Multimedia Applications Platform (OMAP)™ processor(s); a MIPS-baseddesign from MIPS Technologies, Inc. such as MIPS Warrior M-class,Warrior I-class, and Warrior P-class processors; an ARM-based designlicensed from ARM Holdings, Ltd., such as the ARM Cortex-A, Cortex-R,and Cortex-M family of processors; or the like. In some implementations,the data processing device 302 may be a part of a system on a chip (SoC)in which the data processing device 302 and other components are formedinto a single integrated circuit.

Additionally or alternatively, the data processing device 302 mayinclude circuitry such as, but not limited to, one or more afield-programmable devices (FPDs) such as FPGAs; programmable logicdevices (PLDs) such as complex PLDs (CPLDs), high-capacity PLDs(HCPLDs); ASICs such as structured ASICs; programmable SoCs (PSoCs), orcombinations of them, among others. In some examples, the dataprocessing device 302 may include logic blocks or logic fabric, andother interconnected resources that may be programmed to perform variousfunctions, such as the procedures, methods, functions described herein.In some examples, the data processing device 302 may include memorycells (e.g., erasable programmable read-only memory (EPROM),electrically erasable programmable read-only memory (EEPROM), flashmemory, static memory (e.g., static random access memory (SRAM), oranti-fuses)) used to store logic blocks, logic fabric, data, or otherdata in look-up tables (LUTs) and the like.

The baseband circuitry 310310 may be implemented, for example, as asolder-down substrate including one or more integrated circuits, asingle packaged integrated circuit soldered to a main circuit board or amulti-chip module containing two or more integrated circuits.

The antenna beam panel 312 (also called a radio front-end module (RFEM))may comprise a millimeter wave (mmWave) RFEM and one or more sub-mmWaveradio frequency integrated circuits (RFICs). In some examples, the oneor more sub-mmWave RFICs may be physically separated from the mmWaveantenna beam panel 312. The RFICs may include connections to one or moreantennas or antenna arrays, and the antenna beam panel 312 may beconnected to multiple antennas. In some examples, both mmWave andsub-mmWave radio functions may be implemented in the same physicalantenna beam panel 312, which incorporates both mmWave antennas andsub-mmWave. In some implementations, the mmWave functions implement theIEEE 802.11ad and 802.11ay standards.

The platform 300 may also include interface circuitry (not shown) forconnecting external devices with the platform 300. The external devicesconnected to the platform 300 using the interface circuitry includesensor circuitry 221 and electro-mechanical components (EMCs) 222, aswell as removable memory devices coupled to removable memory circuitry223.

The sensor circuitry 304 include devices, modules, or subsystems whosepurpose is to detect events or changes in its environment and send theinformation (e.g., sensor data) about the detected events to one or moreother devices, modules, or subsystems. Examples of such sensors includeinertial measurement units (IMUs) such as accelerometers, gyroscopes, ormagnetometers; microelectromechanical systems (MEMS) ornanoelectromechanical systems (NEMS) including 3-axis accelerometers,3-axis gyroscopes, or magnetometers; level sensors; flow sensors;temperature sensors (e.g., thermistors); pressure sensors; barometricpressure sensors; gravimeters; altimeters; image capture devices (e.g.,cameras or lensless apertures); light detection and ranging (LiDAR)sensors; proximity sensors (e.g., infrared radiation detector and thelike), depth sensors, ambient light sensors, ultrasonic transceivers;microphones or other audio capture devices, or combinations of them,among others.

The system 300 includes one or more motion sensors 304. The sensors 304are configured to generate motion data that represent how the UE ismoving in an environment (e.g., relative to a remote device incommunication with the UE). As previously described, the sensors 304 caninclude one or more accelerometers, one or more gyroscopes and/or othersensing elements. These sensors are further described in relation toFIG. 3. As the pose of the system 300 changes in an environment of thesystem, the sensors 304 capture the motion of the system and send themotion data to a motion detection module 306.

The data processing device 302 is configured to host the motiondetection module 306 and a coverage map module 308. The motion detectionmodule 306 is configured to determine, from the motion data of thesensors 304, how the device is moving in an environment. The motiondetection module 306 can determine a new position and orientation (e.g.,a pose) of the device relative to a prior pose of the device for whichan optimal beam and antenna were selected. The updated pose can beprovided to the coverage map module 308.

The coverage map module 308 is configured to select, based on theupdated pose provided from motion detection module 306, a beam and anantenna of the panel 312 for transmitting or receiving data by thesystem 300. The selection of the beam and the antenna includes aparticular configuration of a selected phased antenna array to generatea directional beam from that array panel. In an example, the dataprocessing device 302 performs the selection process continuously ornearly continuously as the device moves in an environment. In someimplementations, the data processing device 302 performs the selectionprocess with the coverage map module 308 when motion is detected by themotion detection module 306. In some implementations, the dataprocessing device 302 performs the selection process with the coveragemap module 308 when performance drops below a threshold (e.g., when ablockage is detected).

Generally, the data processing device 302 is configured to identify thatan in-use antenna and beam are performing poorly (e.g., below aperformance threshold). For example, a signal strength, a bandwidth, orother link metric (e.g., retrieved from baseband feedback of thebaseband module 310) is associated with a threshold value. When a valueof the metric fails to satisfy the threshold value, the data processingdevice 302 is configured to identify and select a different, optimalantenna and beam for both transmission and reception, without scanningoverhead (e.g., without scanning across some or all of the availableantenna panels and beams). In some implementations, the data processingdevice 302 is configured to determine that the current antenna or beam(or both) will perform poorly in the future (e.g., in 10s ofmilliseconds). The data processing device 302 is configured toanticipate this performance drop and switch to an antenna, beam, or bothfor which a similar performance drop is not expected to occur.

The system 300 receives input from each of the sensors 304 and thebaseband module 310. The baseband (BB) feedback can includesignal-to-noise ratios (SNR), delay spread, angle of arrival (AoA), andsimilar link metrics. The feedback data available from the wirelessbaseband module 310 is used by the data processing device 302 to inferan orientation of wireless dominant paths. Wireless dominant pathsinclude paths that signals follow from the transmitter to the receiver.The data processing device 302 uses the baseband module 310 feedbackdata to identify whether the in-use antenna panel, beam, or both areoptimal. Generally, if the AoA data are not available for the system300, the AoA is estimated by the data processing device 302.

Briefly turning to FIG. 3, devices 400 and 410 show examples of datagathered by sensors 304 of FIG. 2. For example, device 400 includesgyroscopes 402 a, 402 b, and 402 c. The gyroscopes 402 are configured tomeasure a rate at which the device 400 rotates around a spatial axisincluding a rotational pitch, roll, and yaw, movement (e.g., in degreesor radians) of the device 400. Similarly, accelerometers 412 a, 412 b,and 412 c of device 410 are configured to measure changes in velocityalong x, y, and z axes (e.g., translational motion) for the device 410.Devices 400 and 410 are combinable into a single device including bothgyroscope(s) 402 a-c and accelerometer(s) 412 a-c.

Returning to FIG. 2, the motion detection module 306 receivesaccelerometer motion data and identifies a translational movement (e.g.,in centimeters) along each of the x, y, and z axes. The motion detectionmodule 306 receives the gyroscope motion data and determines a rotationof the device around each of the x, y, and z axes. The result is anupdated pose of the system 300 relative to a prior pose of the system.The initial pose of the system is determined relative to the remotedevice connected by the communications link. The initial pose can bedetermined based on AoA data (e.g., from the BB panel 310). In someimplementations, a one-time beam sweep is performed to determine the AoAif the AoA data are not available, as subsequently described. The motiondetection module 306 sends the motion data to the coverage map module308 which is configured for antenna selection, beam selection, or both.The coverage map module 308 determines whether the change in pose issignificant enough for beam or antenna panel switching to occur.

The coverage map module 308 performs selection of the antenna, beam, orboth based on data from the BB panel 310 and the updated pose providedby the motion detection module 306. Because beam radiation patterns andantenna positions are predefined for a given device (e.g., device ofsystem 300), the coverage map module 308 includes coverage map data. Thecoverage map data includes a highest gain antenna panel and beamidentities for each available device orientation and position.

The coverage map module 308 generally selects a new antenna or beambased on two scenarios. A first scenario is a blockage scenario, inwhich Non-Line-of-Sight (NLOS) occurs between the system 300 and theremote device. A second scenario is a mobility scenario in which mobiledevice movement (e.g., of the system or of the remote device) causesantenna or beam misalignment or both antenna and beam misalignment.

In the blockage scenario, the coverage map module 308 detects that theconnection is unstable. This can occur when one or more communicationmetrics (e.g., measured by baseband feedback panel 310) fails to satisfya threshold. Generally, the wireless channel is more stable in LOSenvironment than in a blockage/NLOS environment. When channel stabilityis low, it is likely that there is a NLOS setting or scenario, and abeam or antenna switch (or both) may improve the channel stability. Thedata processing device 302 determines channel stability using thefollowing metrics. The data processing device 302 determines channelstability is low by measuring an SNR drop and contextualizing the dropusing a standard deviation value associated with the SNR. A blockagegenerally results in a significant initial SNR drop and subsequent highSNR deviations. The data processing device 302 determines that thechannel stability is low by measuring delay spread of the signal. Thedelay spread is generally higher in NLOS/blockage settings in comparisonto LOS settings. The data processing device 302 determines that thechannel stability is low by measuring AoA changes. The AoA of thewireless dominant path generally changes when the wireless LOS pathbetween two devices is blocked. In an example, a strongest path for thebeam may become a reflected path rather than a direct path to the remotedevice, as subsequently described in relation to FIG. 6.

In some implementations, the SNR or delay spread values can increase andAoA can change due to mobility, rather than due to blockage. The system300 is configured to differentiate blockage from mobility scenarios bychecking the motion data from the sensors 304. A blockage scenario isdetermined when sensors indicate that the system 300 is static. In someimplementations, the thresholds for the SNR deviation, delay spread, orany other channel metrics are determined by training models prior torun-time (e.g., using machine learning (ML) or similar models. Forexample, a machine learning model can be trained with data includingvarious values of the metrics to classify the signal from the remotedevice as being blocked or unblocked for each of the variouscombinations of values. The machine learning model can be used todetermine the appropriate thresholds for each of the one or more metricsto ensure that a characterization of a signal as being blocked orunblocked represents the correct scenario.

In the movement scenario, the coverage map module 308 is configured todetermine a new antenna or beam (or both) for the system 300 based onthe updated pose provided by the motion detection module 306. The changein pose is determined from a known pose of the system 300 relative tothe remote device. The known pose can be determined (e.g., once) byusing the BB feedback data, such as AoA of a signal. Generally, this canbe determined based on where a highest receive power is present in theantenna array. For example, values of which phi or theta angles areassociated with a highest power can be provided. Generally, the systemassociates the determined AoA with a peak beam of the remotetransmitter. In other words, a strongest lobe estimated to be at theposition of the determined AoA. From the motion data and the AoA, theupdated pose is determined and a new position in a coverage map,subsequently described, is selected. Based on the position in thecoverage map, a particular antenna and beam of the panel 312 are chosenfor transmitting and/or receiving data in the communications link withthe remote device.

As previously described, the system 300 uses baseband feedback toidentify a current orientation of the dominant/strongest wireless pathsto the remote device. When the directions of the wireless paths remainthe same and the device moves, the data processing device 302 uses themotion data to identify the extent of the motion (e.g., in degrees). Thedata processing device 302 is configured to reference the currentdominant signal path orientation and the motion to determine a newwireless path orientation and position (e.g., pose). The data processingdevice 302 uses a coverage map to identify a best antenna array paneland beam for the updated pose. In the mobility LOS scenario, theorientation of the dominant path remains the same while a system 300orientation changes. The data processing device 302 is configured tofetch (or estimate) the AoA of the wireless dominant path P (θ, φ).Using the motion data, the coverage map module 306 identifies that thesystem 300 moved by Δ (θ′, φ′). The coverage map module 306 isconfigured to periodically (e.g., every 10 milliseconds (ms)) fetchgyroscope motion data (e.g., roll, pitch, and yaw). Δ represents adifference between a current pose and the previous pose values. When adominant path direction remains the same over these two iterations (atypical scenario), the dominant path corresponds to device pose P′=P+Δ.When updated device pose P′ aligns with an antenna panel or beam otherthan the in-use antenna panel or beam, the coverage map module 306 isconfigured to cause the system 300 to use the new antenna panel and beam312.

To determine the initial system 300 pose (e.g., orientation andposition) relative to the remote device, the data processing device 302determines or estimates an AoA of transmissions from the remote device.In some implementations, the AoA is provided by receive basebandhardware 310. In some implementations, the data processing device 302estimates AoA from a channel matrix of signal metrics. For example, thedata processing device 302 considers a peak of in-use beam to representa direction of the dominant channel path and thus a current orientationin the beam coverage map. When multiple peaks are found, the dataprocessing device 302 uses a centroid of the peaks to estimate the AoA.The direction of the dominant wireless path represents an orientation ofthe peak beam gain. As previously stated, AoA can be provided by thebaseband module 310 or estimated from the channel matrix, such as byusing a high-resolution direction-finding algorithm based on theeigenvalue decomposition of the sensor covariance matrix observed at thephased arrays (e.g., a multiple signal classification algorithm).

FIGS. 4A-4C illustrate an example of a coverage map 500 a, 500 b, 500 c(collectively coverage map 500) for selection of one or more of anantenna and a beam in accordance with some implementations of thepresent disclosure. Generally, the coverage map module 308 of FIG. 2 ispre-loaded with the coverage map 500. The coverage map 500 specifies,for each particular AoA of the signal, a particular antenna and aparticular beam for the antenna to optimize the channel. For example,the coverage map 500 can be computed in advance of runtime to identify abest antenna and beam at different device orientations towards theantenna of a base station.

The coverage map 500 is defined as a set of entries for each location.For example, a vector such as [phi, theta, best antenna, best beam] canrepresent angles for each best antenna and best beam. While the coveragemap 500 a of FIG. 4A shows only the optimal antenna arrays for anglestheta and phi, a set of maps is used for each other pose value and foreach beam of each antenna. The coverage map module 308 can reference themaps quickly (e.g., within 1 ms) and without requiring scanning of allavailable beams and antenna arrays of the system 300. In coverage map500 a, the optimal beam for each angle theta and phi is omitted forsimplicity of illustration. In an example, the coverage map 500 includesbeams and antenna selections for both rotational and translationalmotion of the motion data.

The coverage map 500 provides an identification of a best antenna paneland beam based on beam radiation patterns. The data processing device302 uses this data in combination with a determination of the wirelessmultipath environment (e.g., azimuth and elevation direction of thewireless path(s)) to identify which beams “align” the best with thewireless dominant path(s). Because the beam radiation patterns andantenna positions are known for a particular device (e.g., a mobiledevice) in advance of runtime, the coverage map can be predefined torepresent a highest gain antenna panel and beam for a given system 300orientation relative to the remote device. As previously described, thedata processing device 302 either estimates or reads from the hardwarethe AoA of the wireless dominant path(s) and identifies the antenna/beamfrom the coverage map 500 which aligns the best with that AoA.

In FIG. 4A, the coverage map 500 a shows antenna selection for givenvalue of theta and phi (pitch and roll) of a mobile device (e.g., system300) with respect to a remote device (e.g., a base station). Based onthe received or estimated AoA data, the initial orientation of themobile device is found to be at about φ=90, θ=90 in the coverage map,corresponding to block 502. Here, antenna 3 is selected (508) as theoptimal antenna. A similar coverage map (not shown) details the optimalbeam for antenna 3 for use in this orientation.

Turning to FIG. 4B, coverage map 500 b shows antenna selection for givenvalue of theta and phi (pitch and roll) of a mobile device (e.g., system300) with respect to a remote device (e.g., a base station). Here, thesystem 300 has changed orientation, rotating along φ to a value ofφ=180, while θ and other position and orientations are static. Thecoverage map shifts from block 502 to block 504. Block 504 indicates(508) that antenna 1 is the optimal antenna for this orientation. Asimilar coverage map (not shown) details the optimal beam for antenna 1for use in this orientation. As the pose at 502 is known already, thedata processing device 302 does not need to estimate the AoA to selectan optimal beam or antenna.

Turning to FIG. 4C, coverage map 500 c shows antenna selection for givenvalue of theta and phi (pitch and roll) of a mobile device (e.g., system300) with respect to a remote device (e.g., a base station). Here, thesystem 300 has changed orientation, rotating along θ to a value ofθ=180, while φ and other position and orientations are static. Thecoverage map shifts from block 504 to block 506. Block 506 indicates(508) that antenna 1 or antenna 3 can be an optimal antenna for thisorientation. A similar coverage map (not shown) details the optimal beamfor antenna 1 and the optimal beam for antenna 3 is for use in thisorientation.

FIG. 5 illustrates an example of an environment 600 for selection by amobile device 602 of one or more of an antenna and a beam based onsensor feedback in accordance with some implementations of the presentdisclosure. In the example environment 600 of FIG. 5, a mobile device(e.g., a mobile phone) is in a first orientation 610 with respect to aremote device 604 (e.g., a gNB). Based on a full beam scan, the device602 identifies a best beam of antenna 2 is used for receiving thesignal. The mobile device 602 also determines the AoA. When the mobiledevice 602 is flipped 180 degrees, the mobile device 602 detects motionfrom gyroscopes coupled to the mobile device. Though the position isstatic, the orientation is changed, and therefore the mobile device 602detects a motion scenario rather than a blocking scenario. Based on themotion data, the mobile device 602 determines an updated pose value. Themobile device 602, using a coverage map, determines that antenna 1 isnow the optimal antenna, and selects a beam from antenna 1 for use inthe communications link with the remote device 604. The mobile device602 selects the new beam and antenna without performing another scan ofthe antennae and beams of the mobile device. The mobile device 602switches from antenna 2 to antenna 1 with low latency (e.g., <1 ms) andwithout the bandwidth overhead of a beam scan.

FIG. 6 illustrates an example environment 700 for selection, by a mobiledevice 702, of one or more of an antenna and a beam based on sensorfeedback in accordance with some implementations of the presentdisclosure. In this example, the mobile device (e.g., a UE) 702 iscommunicating with a remote device 708 (e.g., a gNB). The mobile device702 is static. A first beam 710 a of antenna 2 is initially used forcommunication with the remote device 708 based on a beam scan. Though nomotion occurs, the mobile device 702 detects that the performance of thelink is degraded. For example, there may be an SNR drop, a delay spreadincrease, or changes to an AoA, as previously described. This can be theresult of a blockage 704, such as a person moving between the mobiledevice 702 and the remote device 708, during the communication. Thus,the main lobe of the transmitted signal of the remote device 708 isblocked. In response to detecting the change in values of thecommunications metrics, and in response to also detecting that no motionhas occurred, the mobile device 702 finds a replacement beam 710 b basedon a secondary lobe of the transmitted signal. The secondary lobe isreflected from an object 706 in the environment of the device 702. TheAoA indicates that a signal strength is strongest from a differentposition. The mobile device 702 associates the AoA of the strongestsignal to a location in the coverage map and selects beam 710 b ofantenna 2 as a result.

FIG. 7 illustrates an example process for configuration of parametersfor selection of a beam, a beam, or both based on sensor feedback inaccordance with some implementations of the present disclosure. In someexamples, the electronic device(s), network(s), system(s), chip(s) orcomponent(s), or portions or implementations thereof, of FIGS. 1-6 maybe configured to perform the process 800. The process 800 includesreceiving, at a wireless device, a synchronization signal from a remotedevice. The process 800 includes, in response to receiving thesynchronization signal, obtaining (804) motion data from one or moremotion sensors coupled to the wireless device, the motion dataindicating a change in position or orientation of the wireless device.The process 800 includes determining (806), based on the motion data, apose of the wireless device relative to the remote device. The process800 includes accessing (808) a coverage map that associates, for eachpose of a plurality of poses of the wireless device with respect to theremote device: an antenna for communicating with the remote device; abeam for communicating with the remote device; or both the antenna andthe beam configuration for communicating with the remote device. Theprocess 800 includes selecting (810) a particular antenna and aparticular beam for communicating with the remote device. The process800 includes causing (812) transmission of data to the remote device bythe particular antenna and the particular beam.

In some embodiments, the process 800 includes determining an initialpose of the wireless device with respect to the remote device usingangle of arrival (AoA) data. The pose of the wireless device relative tothe remote device is based on the motion data indicative of the changein the position or the orientation of the wireless device from theinitial pose.

In some embodiments, the motion data is indicative of no change to theposition or orientation of the wireless device over a period of time.The process 800 includes determining that one or more metrics of acommunication channel between the wireless device and the remote devicefail to satisfy one or more respective thresholds. The process 800includes, in response to determining, identifying an angle of arrival(AoA) value of a strongest signal from the remote device. The process800 includes identifying, from the coverage map, the particular beam andthe particular antenna as being associated with the AoA value in thecoverage map.

In some embodiments, the one or more metrics include at least one of asignal to noise (SNR) ratio of the synchronization signal, a delayspread value of the synchronization signal, and a magnitude of a changein the AoA of the synchronization signal.

In some embodiments the process 800 includes selecting the one or morerespective thresholds by applying training data representing values ofthe one or more metrics to a machine learning model. The machinelearning model is configured to classify the synchronization signal asblocked or unblocked.

In some embodiments, the coverage map indicates that the particularantenna and the particular beam represent the highest gain for causingtransmission of data to the remote device or receiving additional datafrom the remote device.

In some embodiments, the one or more sensors comprise at least anaccelerometer, a gyroscope, or both the accelerometer and the gyroscope.

In some embodiments the wireless device and the remote device areconfigured for mmWave communication using frequency range 2 (FR2).

In some embodiments selecting the particular antenna and the particularbeam for communicating with the remote device is performed with alatency of less than 2 milliseconds.

In some embodiments the process 800 includes retrieving motion dataperiodically to determine if the wireless device is moving or is static.

In some embodiments the wireless device comprises at least three antennaarrays, and wherein each antenna array includes at least 10 beamconfigurations.

In some embodiments determining, based on the motion data, the pose ofthe wireless device relative to the remote device includes determiningone or more of a translational motion or a rotational motion of thewireless device exceeds a motion threshold. The process 800 includes, inresponse to determining that the motion threshold is exceeded, accessingthe coverage map.

It is well understood that the use of personally identifiableinformation should follow privacy policies and practices that aregenerally recognized as meeting or exceeding industry or governmentalrequirements for maintaining the privacy of users. In particular,personally identifiable information data should be managed and handledso as to minimize risks of unintentional or unauthorized access or use,and the nature of authorized use should be clearly indicated to users.

Implementations of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, in tangibly embodied computer software or firmware, incomputer hardware, including the structures disclosed in thisspecification and their structural equivalents, or in combinations ofone or more of them. Software implementations of the described subjectmatter can be implemented as one or more computer programs. Eachcomputer program can include one or more modules of computer programinstructions encoded on a tangible, non-transitory, computer-readablecomputer-storage medium for execution by, or to control the operationof, data processing apparatus. Alternatively, or additionally, theprogram instructions can be encoded in/on an artificially generatedpropagated signal. In an example, the signal can be a machine-generatedelectrical, optical, or electromagnetic signal that is generated toencode information for transmission to suitable receiver apparatus forexecution by a data processing apparatus. The computer-storage mediumcan be a machine-readable storage device, a machine-readable storagesubstrate, a random or serial access memory device, or a combination ofcomputer-storage mediums.

The terms “data processing apparatus,” “computer,” and “computingdevice” (or equivalent as understood by one of ordinary skill in theart) refer to data processing hardware. For example, a data processingapparatus can encompass all kinds of apparatus, devices, and machinesfor processing data, including by way of example, a programmableprocessor, a computer, or multiple processors or computers. Theapparatus can also include special purpose logic circuitry including,for example, a central processing unit (CPU), a field programmable gatearray (FPGA), or an application specific integrated circuit (ASIC). Insome implementations, the data processing apparatus or special purposelogic circuitry (or a combination of the data processing apparatus orspecial purpose logic circuitry) can be hardware- or software-based (ora combination of both hardware- and software-based). The apparatus canoptionally include code that creates an execution environment forcomputer programs, for example, code that constitutes processorfirmware, a protocol stack, a database management system, an operatingsystem, or a combination of execution environments. The presentdisclosure contemplates the use of data processing apparatuses with orwithout conventional operating systems, for example LINUX, UNIX,WINDOWS, MAC OS, ANDROID, or IOS.

A computer program, which can also be referred to or described as aprogram, software, a software application, a module, a software module,a script, or code, can be written in any form of programming language.Programming languages can include, for example, compiled languages,interpreted languages, declarative languages, or procedural languages.Programs can be deployed in any form, including as standalone programs,modules, components, subroutines, or units for use in a computingenvironment. A computer program can, but need not, correspond to a filein a file system. A program can be stored in a portion of a file thatholds other programs or data, for example, one or more scripts stored ina markup language document, in a single file dedicated to the program inquestion, or in multiple coordinated files storing one or more modules,sub programs, or portions of code. A computer program can be deployedfor execution on one computer or on multiple computers that are located,for example, at one site or distributed across multiple sites that areinterconnected by a communication network. While portions of theprograms illustrated in the various figures may be shown as individualmodules that implement the various features and functionality throughvarious objects, methods, or processes, the programs can instead includea number of sub-modules, third-party services, components, andlibraries. Conversely, the features and functionality of variouscomponents can be combined into single components as appropriate.Thresholds used to make computational determinations can be statically,dynamically, or both statically and dynamically determined.

The methods, processes, or logic flows described in this specificationcan be performed by one or more programmable computers executing one ormore computer programs to perform functions by operating on input dataand generating output. The methods, processes, or logic flows can alsobe performed by, and apparatus can also be implemented as, specialpurpose logic circuitry, for example, a CPU, an FPGA, or an ASIC.

Computers suitable for the execution of a computer program can be basedon one or more of general and special purpose microprocessors and otherkinds of CPUs. The elements of a computer are a CPU for performing orexecuting instructions and one or more memory devices for storinginstructions and data. Generally, a CPU can receive instructions anddata from (and write data to) a memory. A computer can also include, orbe operatively coupled to, one or more mass storage devices for storingdata. In some implementations, a computer can receive data from, andtransfer data to, the mass storage devices including, for example,magnetic, magneto optical disks, or optical disks. Moreover, a computercan be embedded in another device, for example, a mobile telephone, apersonal digital assistant (PDA), a mobile audio or video player, a gameconsole, a global positioning system (GPS) receiver, or a portablestorage device such as a universal serial bus (USB) flash drive.

Computer readable media (transitory or non-transitory, as appropriate)suitable for storing computer program instructions and data can includeall forms of permanent/non-permanent and volatile/non-volatile memory,media, and memory devices. Computer readable media can include, forexample, semiconductor memory devices such as random access memory(RAM), read only memory (ROM), phase change memory (PRAM), static randomaccess memory (SRAM), dynamic random access memory (DRAM), erasableprogrammable read-only memory (EPROM), electrically erasableprogrammable read-only memory (EEPROM), and flash memory devices.Computer readable media can also include, for example, magnetic devicessuch as tape, cartridges, cassettes, and internal/removable disks.Computer readable media can also include magneto optical disks andoptical memory devices and technologies including, for example, digitalvideo disc (DVD), CD ROM, DVD+/−R, DVD-RAM, DVD-ROM, HD-DVD, and BLURAY.The memory can store various objects or data, including caches, classes,frameworks, applications, modules, backup data, jobs, web pages, webpage templates, data structures, database tables, repositories, anddynamic information. Types of objects and data stored in memory caninclude parameters, variables, algorithms, instructions, rules,constraints, and references. Additionally, the memory can include logs,policies, security or access data, and reporting files. The processorand the memory can be supplemented by, or incorporated in, specialpurpose logic circuitry.

While this specification includes many specific implementation details,these should not be construed as limitations on the scope of what may beclaimed, but rather as descriptions of features that may be specific toparticular implementations. Certain features that are described in thisspecification in the context of separate implementations can also beimplemented, in combination, in a single implementation. Conversely,various features that are described in the context of a singleimplementation can also be implemented in multiple implementations,separately, or in any suitable sub-combination. Moreover, althoughpreviously described features may be described as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can, in some cases, be excised from thecombination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Particular implementations of the subject matter have been described.Other implementations, alterations, and permutations of the describedimplementations are within the scope of the following claims as will beapparent to those skilled in the art. While operations are depicted inthe drawings or claims in a particular order, this should not beunderstood as requiring that such operations be performed in theparticular order shown or in sequential order, or that all illustratedoperations be performed (some operations may be considered optional), toachieve desirable results. In certain circumstances, multitasking orparallel processing (or a combination of multitasking and parallelprocessing) may be advantageous and performed as deemed appropriate.

Moreover, the separation or integration of various system modules andcomponents in the previously described implementations should not beunderstood as requiring such separation or integration in allimplementations, and it should be understood that the described programcomponents and systems can generally be integrated together in a singlesoftware product or packaged into multiple software products.

Accordingly, the previously described example implementations do notdefine or constrain the present disclosure. Other changes,substitutions, and alterations are also possible without departing fromthe scope of the present disclosure.

EXAMPLES

Example 1 includes a method, comprising: obtaining motion data from oneor more motion sensors coupled to a wireless device, the motion dataindicating a change in position or orientation of the wireless device;determining, based on the motion data, a pose of the wireless devicerelative to a remote device; selecting a particular antenna or aparticular beam for communicating with the remote device based on acoverage map that associates, for each pose of a plurality of poses ofthe wireless device with respect to the remote device: an antenna forcommunicating with the remote device; a beam for communicating with theremote device; or both the antenna and the beam configuration forcommunicating with the remote device; and causing transmission orreception of data to or from the remote device by the particular antennaor the particular beam.

Example 2 can include example 1 and further includes determining aninitial pose of the wireless device with respect to the remote deviceusing angle of arrival (AoA) data, wherein the pose of the wirelessdevice relative to the remote device is based on the motion dataindicative of the change in the position or the orientation of thewireless device from the initial pose.

Example 3 includes any of examples 1-2, wherein the motion data isindicative of no change to the position or orientation of the wirelessdevice over a period of time, and wherein the method further comprises:determining that one or more metrics of a communication channel betweenthe wireless device and the remote device fail to satisfy one or morerespective thresholds; in response to determining, identifying an angleof arrival (AoA) value of a strongest signal from the remote device; andidentifying, from the coverage map, the particular beam and theparticular antenna as being associated with the AoA value in thecoverage map.

Example 4 can include any of examples 1-3, wherein the one or moremetrics include at least one of a signal to noise (SNR) ratio of asignal received from the remote device, a delay spread value of thesignal, and a magnitude of a change in the AoA of the signal.

Example 5 can include any of examples 1-4, wherein the coverage mapindicates that the particular antenna and the particular beam representthe highest gain for causing transmission of data to the remote deviceor receiving additional data from the remote device.

Example 6 can include any of examples 1-5, wherein the one or moremotion sensors comprise at least an accelerometer, a gyroscope, or boththe accelerometer and the gyroscope.

Example 7 can include any of examples 1-6, wherein the wireless deviceand the remote device are configured for mmWave communication usingfrequency range 2 (FR2).

Example 8 can include any of examples 1-7, wherein selecting theparticular antenna and the particular beam for communicating with theremote device is performed with a latency of less than 2 milliseconds.

Example 9 can include any of examples 1-8, further comprising retrievingmotion data periodically to determine if the wireless device is movingor is static.

Example 10 can include any of examples 1-9, wherein the wireless devicecomprises at least three antenna arrays, and wherein each antenna arrayincludes at least 10 beam configurations.

Example 11 can include any of examples 1-10, wherein determining, basedon the motion data, the pose of the wireless device relative to theremote device comprises: determining one or more of a translationalmotion or a rotational motion of the wireless device exceeds a motionthreshold; and in response to determining that the motion threshold isexceeded, accessing the coverage map.

Example 12 can include any of examples 1-11, further comprising:comparing the change in position or orientation of the wireless deviceto a threshold change value; and in response to the comparing, accessingthe coverage map when the change exceeds the threshold.

Example 13 can include any of examples 1-12, further comprising:detecting that a signal strength received from the remote device isbelow a threshold signal strength; and in response to detecting,obtaining the motion data.

Example 14 can include any of examples 1-13, further comprising:selecting a particular antenna and or a particular beam forcommunicating with the remote device based on the coverage map; andcausing transmission or reception of data to or from the remote deviceby the particular antenna and the particular beam.

Example 15 includes a wireless device, comprising: at least one motionsensor; one or more antenna arrays each configured for at least two beamconfigurations; one or more processors; and a non-transitorycomputer-readable storage medium storing instructions which, whenexecuted by the one or more processors, cause the one or more processorsto perform operations comprising: obtaining motion data from the atleast one motion sensor, the motion data indicating a change in positionor orientation of the wireless device; determining, based on the motiondata, a change for a pose of the wireless device relative to a remotedevice; selecting a particular antenna and a particular beam forcommunicating with the remote device based on a coverage map thatassociates, for each pose of a plurality of poses of the wireless devicewith respect to the remote device: an antenna array of the one or moreantenna arrays for communicating with the remote device; a beam forcommunicating with the remote device; or both the antenna and the beamfor communicating with the remote device; and causing transmission ofdata to the remote device by the particular antenna and the particularbeam.

Example 16 can include example 15, wherein the operations furthercomprise: determining an initial pose of the wireless device withrespect to the remote device using angle of arrival (AoA) data, whereinthe pose of the wireless device relative to the remote device is basedon the motion data indicative of the change in the position or theorientation of the wireless device from the initial pose.

Example 17 can include any of examples 15-16, wherein the motion data isindicative of no change to the position or orientation of the wirelessdevice over a period of time, and wherein the operations furthercomprise: determining that one or more metrics of a communicationchannel between the wireless device and the remote device fail tosatisfy one or more respective thresholds; in response to determining,identifying an angle of arrival (AoA) value of a strongest signal fromthe remote device; and identifying, from the coverage map, theparticular beam and the particular antenna as being associated with theAoA value in the coverage map.

Example 18 can include any of examples 15-17, wherein the one or moremetrics include at least one of a signal to noise (SNR) ratio of asignal from the remote device, a delay spread value of the signal, and amagnitude of a change in the AoA of the signal.

Example 19 can include any of examples 15-18, wherein the coverage mapindicates that the particular antenna and the particular beam representthe highest gain for causing transmission of data to the remote deviceor receiving additional data from the remote device.

Example 20 can include any of examples 15-19, wherein the one or moremotion sensors comprise at least an accelerometer, a gyroscope, or boththe accelerometer and the gyroscope.

Example 21 can include any of examples 15-20, wherein the wirelessdevice and the remote device are configured for mmWave communicationusing frequency range 2 (FR2).

Example 22 can include any of examples 15-21, the operations furthercomprising: comparing the change in position or orientation of thewireless device to a threshold change value; in response to thecomparing, accessing the coverage map when the change exceeds thethreshold.

Example 23 can include any of examples 15-22, the operations furthercomprising: detecting that a signal strength received from the remotedevice is below a threshold signal strength; and in response todetecting, obtaining the motion data.

Example 24 can include any of examples 15-23, the operations furthercomprising: selecting a particular antenna and or a particular beam forcommunicating with the remote device based on the coverage map; andcausing transmission or reception of data to or from the remote deviceby the particular antenna and the particular beam.

Example 25 can include a processor for a user equipment (UE), theprocessor comprising: circuitry configured to communicate with a remotedevice; and circuitry to execute one or more instructions that, whenexecuted, cause the processor to perform operations comprising:obtaining motion data from one or more motion sensors coupled to awireless device, the motion data indicating a change in position ororientation of the wireless device; determining, based on the motiondata, a pose of the wireless device relative to a remote device;selecting a particular antenna or a particular beam for communicatingwith the remote device based on a coverage map that associates, for eachpose of a plurality of poses of the wireless device with respect to theremote device: an antenna for communicating with the remote device; abeam for communicating with the remote device; or both the antenna andthe beam configuration for communicating with the remote device; andcausing transmission or reception of data to or from the remote deviceby the particular antenna or the particular beam.

Example 26 can include example 25, the operations further comprising:determining an initial pose of the wireless device with respect to theremote device using angle of arrival (AoA) data, wherein the pose of thewireless device relative to the remote device is based on the motiondata indicative of the change in the position or the orientation of thewireless device from the initial pose.

Example 27 can include any of examples 25-26, wherein the motion data isindicative of no change to the position or orientation of the wirelessdevice over a period of time, and the operations further comprising:determining that one or more metrics of a communication channel betweenthe wireless device and the remote device fail to satisfy one or morerespective thresholds; in response to determining, identifying an angleof arrival (AoA) value of a strongest signal from the remote device; andidentifying, from the coverage map, the particular beam and theparticular antenna as being associated with the AoA value in thecoverage map.

Example 28 can include any of examples 25-27, wherein the one or moremetrics include at least one of a signal to noise (SNR) ratio of asignal received from the remote device, a delay spread value of thesignal, and a magnitude of a change in the AoA of the signal.

Example 29 can include any of examples 25-28, wherein the coverage mapindicates that the particular antenna and the particular beam representthe highest gain for causing transmission of data to the remote deviceor receiving additional data from the remote device.

Example 30 can include any of examples 25-29, wherein the one or moremotion sensors comprise at least an accelerometer, a gyroscope, or boththe accelerometer and the gyroscope.

Example 31 can include any of examples 25-30, wherein the wirelessdevice and the remote device are configured for mmWave communicationusing frequency range 2 (FR2).

Example 32 can include any of examples 25-31, wherein selecting theparticular antenna and the particular beam for communicating with theremote device is performed with a latency of less than 2 milliseconds.

Example 33 can include any of examples 25-32, the operations furthercomprising retrieving motion data periodically to determine if thewireless device is moving or is static.

Example 34 can include any of examples 25-33, wherein the wirelessdevice comprises at least three antenna arrays, and wherein each antennaarray includes at least 10 beam configurations.

Example 35 can include any of examples 25-34, wherein determining, basedon the motion data, the pose of the wireless device relative to theremote device comprises: determining one or more of a translationalmotion or a rotational motion of the wireless device exceeds a motionthreshold; and in response to determining that the motion threshold isexceeded, accessing the coverage map.

Example 36 can include any of examples 25-35, the operations furthercomprising: comparing the change in position or orientation of thewireless device to a threshold change value; and in response to thecomparing, accessing the coverage map when the change exceeds thethreshold.

Example 37 can include any of examples 25-36, the operations furthercomprising: detecting that a signal strength received from the remotedevice is below a threshold signal strength; and in response todetecting, obtaining the motion data.

Example 38 can include any of examples 25-37, the operations furthercomprising: selecting a particular antenna and or a particular beam forcommunicating with the remote device based on the coverage map; andcausing transmission or reception of data to or from the remote deviceby the particular antenna and the particular beam.

Example 39 may include a signal as described in or related to any ofexamples 1-67, or portions or parts thereof.

Example 40 may include a datagram, information element, packet, frame,segment, PDU, or message as described in or related to any of examples1-68, or portions or parts thereof, or otherwise described in thepresent disclosure.

Example 41 may include a signal encoded with data as described in orrelated to any of examples 1-38, or portions or parts thereof, orotherwise described in the present disclosure.

Example 42 may include a signal encoded with a datagram, IE, packet,frame, segment, PDU, or message as described in or related to any ofexamples 1-38, or portions or parts thereof, or otherwise described inthe present disclosure.

Example 43 may include an electromagnetic signal carryingcomputer-readable instructions, wherein execution of thecomputer-readable instructions by one or more processors is to cause theone or more processors to perform the method, techniques, or process asdescribed in or related to any of examples 1-38, or portions thereof.

Example 44 may include a computer program comprising instructions,wherein execution of the program by a processing element is to cause theprocessing element to carry out the method, techniques, or process asdescribed in or related to any of examples 1-38, or portions thereof.

Example 45 may include a signal in a wireless network as shown anddescribed herein.

Example 46 may include a method of communicating in a wireless networkas shown and described herein.

Example 47 may include a system for providing wireless communication asshown and described herein.

Example 48 may include a device for providing wireless communication asshown and described herein.

What is claimed is:
 1. A method, comprising: obtaining motion data from one or more motion sensors coupled to a wireless device, the motion data indicating a change in position or orientation of the wireless device; determining, based on the motion data, a pose of the wireless device relative to a remote device; selecting a particular antenna or a particular beam for communicating with the remote device based on a coverage map that associates, for each pose of a plurality of poses of the wireless device with respect to the remote device: an antenna for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and beam configuration for communicating with the remote device; and causing transmission or reception of data to or from the remote device by the particular antenna or the particular beam.
 2. The method of claim 1, further comprising: determining an initial pose of the wireless device with respect to the remote device using angle of arrival (AoA) data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicative of the change in the position or the orientation of the wireless device from the initial pose.
 3. The method of claim 1, wherein the motion data is indicative of no change to the position or orientation of the wireless device over a period of time, and wherein the method further comprises: determining that one or more metrics of a communication channel between the wireless device and the remote device fail to satisfy one or more respective thresholds; in response to determining, identifying an angle of arrival (AoA) value of a strongest signal from the remote device; and identifying, from the coverage map, the particular beam and the particular antenna as being associated with the AoA value in the coverage map.
 4. The method of claim 3, wherein the one or more metrics include at least one of a signal to noise (SNR) ratio of a signal received from the remote device, a delay spread value of the signal, and a magnitude of a change in the AoA of the signal.
 5. The method of claim 1, wherein the coverage map indicates that the particular antenna and the particular beam represent the highest gain for causing transmission of data to the remote device or receiving additional data from the remote device.
 6. The method of claim 1, wherein the one or more motion sensors comprise at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope.
 7. The method of claim 1, wherein the wireless device and the remote device are configured for mmWave communication using frequency range 2 (FR2).
 8. The method of claim 1, wherein selecting the particular antenna and the particular beam for communicating with the remote device is performed with a latency of less than 2 milliseconds.
 9. The method of claim 1, further comprising retrieving motion data periodically to determine if the wireless device is moving or is static.
 10. The method of claim 1, wherein the wireless device comprises at least three antenna arrays, and wherein each antenna array includes at least 10 beam configurations.
 11. The method of claim 1, wherein determining, based on the motion data, the pose of the wireless device relative to the remote device comprises: determining one or more of a translational motion or a rotational motion of the wireless device exceeds a motion threshold; and in response to determining that the motion threshold is exceeded, accessing the coverage map.
 12. The method of claim 1, further comprising: comparing the change in position or orientation of the wireless device to a threshold change value; and in response to the comparing, accessing the coverage map when the change exceeds the threshold.
 13. The method of claim 1, further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; and in response to detecting, obtaining the motion data.
 14. The method of claim 1, further comprising: selecting a particular antenna and or a particular beam for communicating with the remote device based on the coverage map; and causing transmission or reception of data to or from the remote device by the particular antenna and the particular beam.
 15. A wireless device, comprising: at least one motion sensor; one or more antenna arrays each configured for at least two beam configurations; one or more processors; and a non-transitory computer-readable storage medium storing instructions which, when executed by the one or more processors, cause the one or more processors to perform operations comprising: obtaining motion data from the at least one motion sensor, the motion data indicating a change in position or orientation of the wireless device; determining, based on the motion data, a change for a pose of the wireless device relative to a remote device; selecting a particular antenna and a particular beam for communicating with the remote device based on a coverage map that associates, for each pose of a plurality of poses of the wireless device with respect to the remote device: an antenna array of the one or more antenna arrays for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and the beam for communicating with the remote device; and causing transmission of data to the remote device by the particular antenna and the particular beam.
 16. The wireless device of claim 15, wherein the operations further comprise: determining an initial pose of the wireless device with respect to the remote device using angle of arrival (AoA) data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicative of the change in the position or the orientation of the wireless device from the initial pose.
 17. The wireless device of claim 15, wherein the motion data is indicative of no change to the position or orientation of the wireless device over a period of time, and wherein the operations further comprise: determining that one or more metrics of a communication channel between the wireless device and the remote device fail to satisfy one or more respective thresholds; in response to determining, identifying an angle of arrival (AoA) value of a strongest signal from the remote device; and identifying, from the coverage map, the particular beam and the particular antenna as being associated with the AoA value in the coverage map.
 18. The wireless device of claim 17, wherein the one or more metrics include at least one of a signal to noise (SNR) ratio of a signal from the remote device, a delay spread value of the signal, and a magnitude of a change in the AoA of the signal.
 19. The wireless device of claim 15, wherein the coverage map indicates that the particular antenna and the particular beam represent the highest gain for causing transmission of data to the remote device or receiving additional data from the remote device.
 20. The wireless device of claim 15, wherein the one or more motion sensors comprise at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope.
 21. The wireless device of claim 15, wherein the wireless device and the remote device are configured for mmWave communication using frequency range 2 (FR2).
 22. The wireless device of claim 15, the operations further comprising: comparing the change in position or orientation of the wireless device to a threshold change value; and in response to the comparing, accessing the coverage map when the change exceeds the threshold.
 23. The wireless device of claim 15, the operations further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; and in response to detecting, obtaining the motion data.
 24. The wireless device of claim 15, the operations further comprising: selecting a particular antenna and or a particular beam for communicating with the remote device based on the coverage map; and causing transmission or reception of data to or from the remote device by the particular antenna and the particular beam.
 25. A processor for a user equipment (UE), the processor comprising: circuitry configured to communicate with a remote device; and circuitry to execute one or more instructions that, when executed, cause the processor to perform operations comprising: obtaining motion data from one or more motion sensors coupled to a wireless device, the motion data indicating a change in position or orientation of the wireless device; determining, based on the motion data, a pose of the wireless device relative to a remote device; selecting a particular antenna or a particular beam for communicating with the remote device based on a coverage map that associates, for each pose of a plurality of poses of the wireless device with respect to the remote device: an antenna for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and beam configuration for communicating with the remote device; and causing transmission or reception of data to or from the remote device by the particular antenna or the particular beam.
 26. The processor of claim 25, the operations further comprising: determining an initial pose of the wireless device with respect to the remote device using angle of arrival (AoA) data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicative of the change in the position or the orientation of the wireless device from the initial pose.
 27. The processor of claim 25, wherein the motion data is indicative of no change to the position or orientation of the wireless device over a period of time, and the operations further comprising: determining that one or more metrics of a communication channel between the wireless device and the remote device fail to satisfy one or more respective thresholds; in response to determining, identifying an angle of arrival (AoA) value of a strongest signal from the remote device; and identifying, from the coverage map, the particular beam and the particular antenna as being associated with the AoA value in the coverage map.
 28. The processor of claim 27, wherein the one or more metrics include at least one of a signal to noise (SNR) ratio of a signal received from the remote device, a delay spread value of the signal, and a magnitude of a change in the AoA of the signal.
 29. The processor of claim 25, wherein the coverage map indicates that the particular antenna and the particular beam represent the highest gain for causing transmission of data to the remote device or receiving additional data from the remote device.
 30. The processor of claim 25, wherein the one or more motion sensors comprise at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope.
 31. The processor of claim 25, wherein the wireless device and the remote device are configured for mmWave communication using frequency range 2 (FR2).
 32. The processor of claim 25, wherein selecting the particular antenna and the particular beam for communicating with the remote device is performed with a latency of less than 2 milliseconds.
 33. The processor of claim 25, the operations further comprising retrieving motion data periodically to determine if the wireless device is moving or is static.
 34. The processor of claim 25, wherein the wireless device comprises at least three antenna arrays, and wherein each antenna array includes at least 10 beam configurations.
 35. The processor of claim 25, wherein determining, based on the motion data, the pose of the wireless device relative to the remote device comprises: determining one or more of a translational motion or a rotational motion of the wireless device exceeds a motion threshold; and in response to determining that the motion threshold is exceeded, accessing the coverage map.
 36. The processor of claim 25, the operations further comprising: comparing the change in position or orientation of the wireless device to a threshold change value; and in response to the comparing, accessing the coverage map when the change exceeds the threshold.
 37. The processor of claim 25, the operations further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; and in response to detecting, obtaining the motion data.
 38. The processor of claim 25, the operations further comprising: selecting a particular antenna and or a particular beam for communicating with the remote device based on the coverage map; and causing transmission or reception of data to or from the remote device by the particular antenna and the particular beam. 